Automatic Animation of Hair Blowing in Still Portrait Photos

Wenpeng Xiao, Wentao Liu, Yitong Wang, Bernard Ghanem, Bing Li; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 22963-22975

Abstract


We propose a novel approach to animate human hair in a still portrait photo. Existing work has largely studied the animation of fluid elements such as water and fire. However, hair animation for a real image remains underexplored, which is a challenging problem, due to the high complexity of hair structure and dynamics. Considering the complexity of hair structure, we innovatively treat hair wisp extraction as an instance segmentation problem, where a hair wisp is referred to as an instance. With advanced instance segmentation networks, our method extracts meaningful and natural hair wisps. Furthermore, we propose a wisp-aware animation module that animates hair wisps with pleasing motions without noticeable artifacts. The extensive experiments show the superiority of our method. Our method provides the most pleasing and compelling viewing experience in the qualitative experiments, and outperforms state-of-the-art still-image animation methods by a large margin in the quantitative evaluation. Project url: https://nevergiveu.github.io/AutomaticHairBlowing/

Related Material


[pdf] [supp] [arXiv]
[bibtex]
@InProceedings{Xiao_2023_ICCV, author = {Xiao, Wenpeng and Liu, Wentao and Wang, Yitong and Ghanem, Bernard and Li, Bing}, title = {Automatic Animation of Hair Blowing in Still Portrait Photos}, booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)}, month = {October}, year = {2023}, pages = {22963-22975} }